<p>This study presents statistical land use regression models to characterize the spatial distribution of two air pollutants: nitrogen dioxide (NO<sub>2</sub>) and sulphur dioxide (SO<sub>2</sub>). While nitrogen dioxide (NO<sub>2</sub>) is considered to be a marker of vehicular pollution, sulphur dioxide (SO<sub>2</sub>) is a major industrial emission. The research uses mobile field- monitored pollution measurement data at over 2000 locations across the Hamilton Census Metropolitan area (CMA) during November 2005-March 2006. Various land use characteristics, transportation attributes and meteorological characteristics are used in the model to explain the spatial variations in the concentration of the pollutants. A key contribution of the paper is that it explicitly includes wind directions (i.e. north-east, north-west, south-west and south-east) into the models.</p> <p>The results reveal that proximity to the major roads and highways, total length of roads nearby, traffic volume, nearby park and commercial areas, distance to the lakeshore industries and wind speed have major impact on NO<sub>2</sub> concentration. While proximity to the roads and highways and higher total length of roads nearby increases the concentration of NO<sub>2</sub>, higher amount of nearby park areas and wind speed decreases the level of concentration of the pollutant. For north-east direction distance to major roads and highways, lakeshore industries, and wind speed has significant impact on the concentration level. While for the north-west direction, commercial area within 350 meter, distance to QEW and Centennial Parkway North intersection contribute significantly to the concentration of NO<sub>2</sub>, total length of the roads within 50 meter from the observation points and distance to the railway are significantly associated with the concentration level in case of south-east wind direction model. Lastly, the significance of a dummy variable indicates that the upper city has lower concentration of NO<sub>2</sub> compared to the lower city according to the south-west wind direction model.</p> <p>For the SO<sub>2</sub> models, the results suggest that proximity to downwind locations from the industries, proximity to commercial and park areas, and proximity to the Bay Front Area play a role to the concentration of the pollutant. While downwind location with closeness to the industries increases the level of concentration of SO<sub>2, </sub>higher wind speed and proximity to the Bay Front Area reduces the level of pollution in general.</p> <p>All models for NO<sub>2</sub> and SO<sub>2</sub> provide reasonable model fit in terms of coefficient of determination (R<sup>2</sup>) of the estimated land use regression models for different major wind directions. Almost all parameters are statistically significant at least at the 5% level of significance. The estimated models are used to generate pollution surfaces for the Hamilton CMA. The resulting spatial distribution of pollution concentration can be useful for informing policy.</p>